Chapters authored
Sentiment Analysis of Social Media Using Artificial Intelligence
Social media refers to the development and sharing of sentiment, information, and interests, as well as other forms of opinion via virtual communities and networks. Nowadays, social networking and micro blogging websites are considered reliable sources of information since users may openly express their opinions in these forums. An investigation of the sentiment on social media could assist decision-makers in learning how consumers feel about their services, products, or policies. Extracting emotion from social media messages is a difficult task due to the difficulty of Natural Language Processing (NLP). These messages frequently use a combination of graphics, emoticons, text, etc. to convey the sentiment or opinion of the general people. These claims, known as eWOM (Electronic Word of Mouth), are quite common in public forums where people may express their opinions. A classification issue arises when categorizing the sentiment of eWOM as positive, negative, or neutral. We could not use standard NLP tools to examine social media sentiment. In this chapter, we will study the role of Artificial Intelligence in identifying the sentiment polarity of social media. We will apply ML(Machine Learning) methods to resolve this classification issue without diving into the difficulty of eWOM parsing.
Part of the book: Advances in Sentiment Analysis